Using our sparse representation based variable selection (SRVS) based integrated analysis of gene expression and SNP data sets, we ranked 11522 gene expression probes and 354893 SNPs and then performed an enrichment analysis on each of the top 1000 variables selected. Results showed that 559 variables (SNPs/gene expressions), corresponding to 330 genes, may serve as potential biomarkers for blood pressure related disease (LOD score>3). Nevertheless, a portion of the selected variables are likely to be false positives. Molecular validation is needed before any solid conclusions can be made. However, the results obtained from the current study seem to indicate the promise of the SRVS algorithm in analyzing multiple data sets of different structures for a comprehensive analysis.